Primary Location: Cambridge
Additional: Gothenburg; Warsaw
Build a long-term career by unlocking opportunities for lifelong learning
Build unrivalled capabilities in a place that promotes learning agility and offers development opportunities. We never stand still so you’ll have the chance to constantly grow your abilities, skills and knowledge.
Here we are a fusion of challenging and interesting work, in an energising and inspiring environment. Embrace the opportunity for development – whether that’s upskilling or reskilling.
We are reimagining what a culture of lifelong learning means. Because we want all our people to embrace the challenges and opportunities that lie ahead. This is the place to build a long-term career.
Have the freedom to change how things are done. Powered by our spirit of curiosity we are constantly reimagining and reframing what the future looks like. Here, each of us is empowered to innovate and take smart risks that will change our course.
- Perform technical and data analysis work to establish requirements for new data preparation projects.
- Design data preparation workflows and define outputs (e.g., proposed data models and modes of access) and success criteria for projects.
- Request and setup appropriate analytical environments a to achieve data preparation and data-scientific outcomes.
- Perform data wrangling, cleaning, combining, transformation, cross-linkage etc. to build new datasets that enable specific data-scientific research workflows to be conducted to a high quality and in an accelerated manner.
- Generating reusable scripting and code notebooks for sharing with other team members.
- Planning data verification and testing plans, including user acceptance testing and user handover (data, code, information ‘readmes’)
- Active team-worker to help to maintain an encouraging, agile and outcomes-focused culture.
- Excellent skills in one or multiple scripting and programming languages to (Python, R, SQL etc)!
- Experience of data analysis profiling, investigating, interpreting and detailing data requirements, e.g. data modelling techniques and hands on modelling experience.
- Basic understanding of clinical trials data structure.
- Good awareness of a range of data & analytics patterns including distributed computing (Hadoop/Spark), NoSQL, virtualization, data streaming, container technology (e.g., Docker), traditional warehousing.
- Knowledge and preferably experience of the Big-Data ecosystem.
- Experience of agile working practices, e.g., Scrum!
- Solid grasp of applied mathematical, machine learning and AI techniques and workflows.
- Degree in life sciences/economics/computer science is a plus, but not crucial.
Why we love it
If your passion is science and you want to be part of a team that makes a bigger impact on patients’ lives, then there’s no better place to be. Here we truly understand science and apply it every day to strengthen and grow our pipeline.
So, what’s next?
- Are you already imagining yourself joining our team? Good, because we can’t wait to hear from you.
- Are you ready to bring new ideas and fresh thinking to the table? Brilliant! We have one seat available and we hope it’s yours.
Where can I find out more?
Our Social Media, Follow AstraZeneca on LinkedIn https://www.linkedin.com/company/1603/
Follow AstraZeneca on Facebook https://www.facebook.com/astrazenecacareers/
Follow AstraZeneca on Instagram https://www.instagram.com/astrazeneca_careers/?hl=en
AstraZeneca embraces diversity and equality of opportunity. We are committed to building an inclusive and diverse team representing all backgrounds, with as wide a range of perspectives as possible, and harnessing industry-leading skills. We believe that the more inclusive we are, the better our work will be. We welcome and consider applications to join our team from all qualified candidates, regardless of their characteristics. We comply with all applicable laws and regulations on non-discrimination in employment (and recruitment), as well as work authorisation and employment eligibility verification requirements.